chainer.dataset.DatasetMixin¶
- class chainer.dataset.DatasetMixin[source]¶
Default implementation of dataset indexing.
DatasetMixin provides the
__getitem__()
operator. The default implementation usesget_example()
to extract each example, and combines the results into a list. This mixin makes it easy to implement a new dataset that does not support efficient slicing.Dataset implementation using DatasetMixin still has to provide the
__len__()
operator explicitly.Methods
- __getitem__(index)[source]¶
Returns an example or a sequence of examples.
It implements the standard Python indexing and one-dimensional integer array indexing. It uses the
get_example()
method by default, but it may be overridden by the implementation to, for example, improve the slicing performance.- Parameters
index (int, slice, list or numpy.ndarray) – An index of an example or indexes of examples.
- Returns
If index is int, returns an example created by get_example. If index is either slice or one-dimensional list or numpy.ndarray, returns a list of examples created by get_example.
Example
>>> import numpy >>> from chainer import dataset >>> class SimpleDataset(dataset.DatasetMixin): ... def __init__(self, values): ... self.values = values ... def __len__(self): ... return len(self.values) ... def get_example(self, i): ... return self.values[i] ... >>> ds = SimpleDataset([0, 1, 2, 3, 4, 5]) >>> ds[1] # Access by int 1 >>> ds[1:3] # Access by slice [1, 2] >>> ds[[4, 0]] # Access by one-dimensional integer list [4, 0] >>> index = numpy.arange(3) >>> ds[index] # Access by one-dimensional integer numpy.ndarray [0, 1, 2]
- get_example(i)[source]¶
Returns the i-th example.
Implementations should override it. It should raise
IndexError
if the index is invalid.- Parameters
i (int) – The index of the example.
- Returns
The i-th example.
- __eq__(value, /)¶
Return self==value.
- __ne__(value, /)¶
Return self!=value.
- __lt__(value, /)¶
Return self<value.
- __le__(value, /)¶
Return self<=value.
- __gt__(value, /)¶
Return self>value.
- __ge__(value, /)¶
Return self>=value.